Deep neural network for remote-sensing image interpretation: status and perspectives

• 来源期刊: 国家科学评论（英文版）
• 年，卷（期）: 2019,（6）
• 页码范围: 1082-1086
• 页数: 5页
• 语种: 英文
• DOI: 10.1093/nsr/nwz058

摘要

Deep neural networks (DNNs) refer to end-to-end mappings (i.e.from data to information) by stacking a large number of filters learned from massive samples.By courtesy of the comprehensive Earth observation platforms and convenient data access,remote-sensing practitioners are dealing with very large and ever-growing data volumes,which call for fast and transferrable machine-learning technologies for the large-scale geospatial information mining [1].